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Sensitivity Analysis for a Scenario-Based Reliability Prediction Model

Rodrigues, G; Rosenblum, D; Uchitel, S; (2005) Sensitivity Analysis for a Scenario-Based Reliability Prediction Model. In: Proceedings ICSE 2005 Workshop on Architecting Dependable Systems. (pp. 73-77). ACM Press: USA. Green open access

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Abstract

As a popular means for capturing behavioural requirements, scenariosshow how components interact to provide system-level functionality.If component reliability information is available, scenarioscan be used to perform early system reliability assessment. Inprevious work we presented an automated approach for predictingsoftware system reliability that extends a scenario specificationto model (1) the probability of component failure, and (2) scenariotransition probabilities. Probabilistic behaviour models ofthe system are then synthesized from the extended scenario specification.From the system behaviour model, reliability predictioncan be computed. This paper complements our previous work andpresents a sensitivity analysis that supports reasoning about howcomponent reliability and usage profiles impact on the overall systemreliability. For this purpose, we present how the system reliabilityvaries as a function of the components reliabilities and thescenario transition probabilities. Taking into account the concurrentnature of component-based software systems, we also analysethe effect of implied scenarios prevention into the sensitivity analysisof our reliability prediction technique.

Type: Book chapter
Title: Sensitivity Analysis for a Scenario-Based Reliability Prediction Model
Open access status: An open access version is available from UCL Discovery
Additional information: Imported via OAI, 7:29:01 5th Jul 2005
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/693
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